Connected beta study route · academic review pending

AWS Certified Machine Learning Engineer - Associate

DASKEREL beta · internal AI review pending

Amazon Web Services · associate stage · data ai

Exam code: MLA-C01

Exam version update: AWS announced an MLA-C02 transition beginning in September 2026. Confirm the active exam code and language dates before publication or booking.

Use the suggested DASKEREL lessons below to build subject foundations and practical evidence. The related domain mocks test DASKEREL subjects, not this awarding body's exam. Credential-specific syllabus mapping and academic review remain pending.

Open study routeCheck official sources

Learn the underlying subject

These tracks are selected for subject relevance. Open a track to see its full lessons, exercises and study sequence.

Machine Learning Engineer

Learn practical ML foundations, feature engineering, model training, evaluation, deployment, monitoring, governance, and MLOps workflows.

Suggested lessons for this credential

Selected from the credential title and practical evidence tasks. Compare with the awarding body's current guide; this is not an exam-objective map.

  1. AWS Certified Machine Learning Engineer - Associate
  2. Machine learning foundations
  3. Data preparation and features
  4. Model evaluation metrics
  5. Model deployment
  6. MLOps monitoring and governance
All lessons and labsRelated subject domain mock

MLOps Engineer

Build production MLOps skills across dataset versioning, feature pipelines, experiment tracking, model registry, CI/CD, deployment, monitoring, drift detection, governance, cost, and safe rollback.

Suggested lessons for this credential

Selected from the credential title and practical evidence tasks. Compare with the awarding body's current guide; this is not an exam-objective map.

  1. MLOps foundations and operating model
  2. Batch real-time and edge model deployment
  3. Model monitoring drift bias latency and cost
All lessons and labsRelated subject domain mock

Build practical evidence

Choose a realistic case, record assumptions, carry out the work safely and reflect on what the result demonstrates.

Evidence ideas

  • Model card
  • Evaluation report
  • Deployment and monitoring record

Portfolio work supports career discussion. It does not satisfy formal eligibility or certification requirements unless the awarding body confirms it.

Original DASKEREL practice · controlled beta

Applied practice: AWS Certified Machine Learning Engineer - Associate

Work through 3 written tasks. Choose a 20-minute timer or work without a timer. This is an unscored learning diagnostic, not a reproduction or prediction of the awarding body's examination.

Check before booking

  1. Read the awarding body's current exam guide and compare every objective with your completed lessons.
  2. Check eligibility, experience, exam version, language, price, accommodations and renewal rules.
  3. Use the related DASKEREL domain practice to find weak fundamentals; use official sample material where offered for exam format.
  4. Record gaps and return to the appropriate track or an approved provider resource before the assessment.